First-in-human immunoPET imaging of COVID-19 convalescent patients using dynamic total-body PET and a CD8-targeted minibody

With most of the T cells residing in the tissue, not the blood, developing noninvasive methods for in vivo quantification of their biodistribution and kinetics is important for studying their role in immune response and memory. This study presents the first use of dynamic positron emission tomography (PET) and kinetic modeling for in vivo measurement of CD8+ T cell biodistribution in humans. A 89Zr-labeled CD8-targeted minibody (89Zr-Df-Crefmirlimab) was used with total-body PET in healthy individuals (N = 3) and coronavirus disease 2019 (COVID-19) convalescent patients (N = 5). Kinetic modeling results aligned with T cell–trafficking effects expected in lymphoid organs. Tissue-to-blood ratios from the first 7 hours of imaging were higher in bone marrow of COVID-19 convalescent patients compared to controls, with an increasing trend between 2 and 6 months after infection, consistent with modeled net influx rates and peripheral blood flow cytometry analysis. These results provide a promising platform for using dynamic PET to study the total-body immune response and memory.


Table S2. Microparameters of model fits in all organs-of-interest of individual subjects.
Microparameters of AIC-preferred model fit results for lungs, spleen, sacrum, ilium, tonsils, and occipital lymph nodes shown for all subjects with dynamic scans.K1 is shown in mlplasma/min/mltissue, and k2, k3, and k4 are shown in 1/min.Ki is calculated by   Table S5.Flow cytometry panel design used for cell immunophenotyping.All antibodies and viability dyes were titrated to determine the optimal concentration for each assay.
Table S6.Flow cytometry panel design used for intracellular cytokine staining assays.All antibodies and viability dyes were titrated to determine the optimal concentration for each assay.

Fig. S1 .
Fig. S1.Whole-blood clearance biological half-lives.Biological half-lives derived from triexponential fitting on the whole-blood TACs of 6 subjects (9 scans), including (A) the initial, (B) the intermediate, and (C) the terminal elimination phases.Image-derived LV blood pool was used for obtaining the whole-blood TACs.With a very low uptake in the myocardium, negligible effects from myocardium spill-over on LV blood pool were observed.

Fig. S2 .
Fig. S2.PET/CT images of selected occipital lymph nodes.Transverse PET/CT slices through representative occipital lymph nodes selected in each subject (marked with arrows), which have been used for kinetic modeling.For COVID-19 patients (Sub01 to Sub05), only the baseline scans are shown.

Fig. S3 .
Fig. S3.Percentage changes of SUV at the 48-h relative to the 6-h timepoint.Percentage changes of SUV at the 48-h relative to the 6-h timepoint show similar trends in all subjects, in different regions of bone marrow (vertebrae, sacrum, and ilium), spleen, tonsils, and lymph nodes.The percentage changes of SUV in the lymph nodes represent the average SUV changes in 11-22 head and neck lymph nodes for each subject.

Fig. S4 .
Fig. S4.Decay-corrected TBR curves in different organs-of-interest.TBRs are shown as a function of time for bone marrow, spleen, occipital lymph nodes, tonsils, liver, lungs, and nasal cavity (A) during the 48-h of the imaging study and (B) during the first 90-min after tracer administration for all subjects.

Fig. S5 .
Fig. S5.AIC model selection results in all organs-of-interest.AIC values of 1T3P, 2T4P, and 2T5P model fittings performed on the lungs, spleen, bone marrow (sacrum and ilium), tonsils, and selected occipital lymph nodes of all subjects.

Fig. S6 .
Fig. S6.Examples of model fits in a COVID-19 convalescent subjects.Results of 1T3P, 2T4P, and 2T5P model fittings performed on the lungs, spleen, bone marrow (sacrum and ilium), tonsils, and selected occipital lymph nodes of the baseline scans of an example COVID-19 patient (Sub02) shown for (A) the 0-48 h and (B) zoomed on the 0-90 min.

Fig. S8 .
Fig. S8.Normalized sensitivity plots of microparameters of the AIC-preferred model.Normalized sensitivities of microparameters of the model with average highest AIC, shown for lungs, spleen, sacrum, ilium, tonsils, and occipital lymph node of the baseline scans of an example COVID-19 patient (Sub02) shown for the 0-48 h.

Fig. S9 .
Fig. S9.Patlak plots of different organs-of-interest.Patlak plots of different regions of bone marrow, spleen, occipital lymph nodes, tonsils, liver, lungs, and nasal cavity shown (A) during the 48-h of the imaging study and (B) during the first 90-min after tracer administration for all subjects with dynamic scans.

Fig. S10 .
Fig. S10.Effect of late-timepoint weighting factors on model fitting in spleen.Results of 1T3P, 2T4P, and 2T5P model fittings performed on spleen of the baseline scans of an example COVID-19 patient (Sub02) shown for (A) the 0-48 h and (B) zoomed on the 0-90 min, using increased weighting factors (×10 compared to previous fits) for the two late timepoint scans.

Fig. S11 .
Fig. S11.Changes in concentrations of 2T5P model compartments as a function of time.Concentrations of the compartments of the 2T5P model fit performed on (A) lungs, (B) spleen and bone marrow ((C) sacrum and (D) ilium) of the baseline scans of an example COVID-19 patient (Sub02) shown for the 0-48 h of the imaging, including the concentrations of free tracer in tissue (CFree), bound tracer in tissue (CBound) and the tissue blood fraction (CBlood), in which CT = CFree + CBound + CBlood.

Fig. S12 .
Fig. S12.CT image slices through the thymus of all subjects.Selected slices through low-dose CT images of all subjects are compared with the corresponding thymus fatty degeneration assigned to each subject.

Fig. S13 .
Fig. S13.Peripheral blood CD4 + T cell phenotyping.(A) Percentage of CD4 + T cells within the live CD3 + population, (B) percentage of activated CD4 + T cells characterized by CD38 and HLA-DR co-expression and (C) CD56 expression, and (D) percentage of exhausted CD4 + T cells characterized by PD-1 expression in all subjects.

Fig. S14 .
Fig. S14.Memory subsets of CD8 + and CD4 + T cells.Memory subsets of (A) CD8 + and (B) CD4 + T cells, comparing the percentage of naïve, central memory, effector memory, and TEMRA cells in peripheral blood of all subjects.

Fig. S16 .
Fig. S16.Total responses in CD8 + and CD4 + memory T cells.Total percentage of (A and B) CD8 + and (C and D) CD4 + memory T cells responding in any way (CD107a, IFNγ, IL2, MIP-1β, or TNFα) to SARS-CoV-2 (A and C) spike and (B and b) nucleocapsid proteins compared in peripheral blood of all subjects.

Fig. S19 .
Fig. S19.Polyfunctional responses in SARS-CoV-2 spike-specific and nucleocapsid-specific CD8 + memory T cells.The percentages shown on each pie chart represent the median magnitude of the total response in each group.

Fig. S20 .
Fig. S20.Polyfunctional responses in SARS-CoV-2 spike-specific and nucleocapsid-specific CD4 + memory T cells.The percentages shown on each pie chart represent the median magnitude of the total response in each group.

Fig. S23 .
Fig. S23.Gating strategy for T cell immunophenotyping.Single cell lymphocytes were gated, aggregates removed, and stained with LIVE/DEAD cell stain kit to exclude non-viable cells.Viable CD3 + cells were gated as T cells and CD8 + and CD4 + T cells were separated.

Fig. S26 .
Fig. S26.Gating strategies to define SARS-CoV-2-specific CD8+ memory T cell response, using individual SARS-CoV-2 peptide pools.Representative examples of flow cytometry plots of SARS-CoV-2-specific CD8 + memory T cells are shown after overnight stimulation with spike and nucleocapsid peptide pools, compared to negative control (DMSO) and positive control stimulation with SEB.

Table S3 . Correlation matrix of model microparameters. Correlation
matrix of microparameters of the AIC-preferred model is presented for lungs, spleen, sacrum, ilium, tonsils, and occipital lymph nodes, showing mean and standard deviations calculated over all subjects with 90-min dynamic scans.

Table S4 .
Estimated errors of model microparameters.Bias (%), standard deviation (%), and RMSE (%) of the AIC-preferred model microparameters in lungs, spleen, sacrum, ilium, tonsils, and cervical lymph nodes, calculated from model fitting on 100 simulated TACs generated for each subject from the calculated noise model of the measured TAC.The results show the averaged values among all subjects with 90-min dynamic scans.